code: def _validate_cluster_number(original_results, n_clusters):
      """validate all estimators form the same number of clusters as defined
      in n_clusters.
  
      Parameters
      ----------
      original_results :
      n_clusters
  
      Returns
      -------
  
      """
      original_results = check_array(original_results)
  
      for i in range(original_results.shape[1]):
          values, counts = np.unique(
              original_results[:, i], return_counts=True
          )
          if len(values) != n_clusters:
              print(len(values), len(counts))
              RuntimeError(
                  "cluster result does not equal to n_clusters"
              )
  
      return original_results
  
file_path: combo/combo/models/cluster_comb.py
imports: import numpy
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
  from numpy.testing import assert_equal
  from pyod.utils.utility import check_parameter
  from .base import BaseAggregator
  from .score_comb import majority_vote
label_desc: Use image node_id 4 for calling a global function with example usage: _validate_cluster_number(original_results, n_clusters) and returns: original_results